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H: suggest ingredients based on recipe title
I would like to construct system that would suggest user ingredients once he/she inputs title of the recipe.
I think that this is the task of machine learning or AI, but on the other hand I am pretty new to ML and generally in AI development and I feel kinda lost, since I d... |
H: Dueling DQN what does a' mean?
what does $a'$ mean in the "combining" equation in Dueling DQN? (top of the page 5)
$$Q(s,a; \theta, \alpha, \beta) = V(s; \theta, \beta) + \biggl( A(s, a; \theta, \alpha) - \frac{1}{N}\sum_{a'}^{N}A(s, a'; \theta, \alpha) \biggr)$$
Where there are $N$ actions to choose from;
$s$ is ... |
H: Reframing action recognition as a reinforcement learning problem
Given the significant advancements in reinforcement learning, I wanted to know whether it is possible to recast problems such as action recogniton, object tracking, or image classification into reinforcement learning problems.
AI: Given the significan... |
H: R: for each row in DF1 subset/count corresponding rows in DF2
How can I subset/count rows in one data frame that correspond to rows in another data frame?
I have a data frame DF1 with dates, categories and time instances for each of the date and category combinations. For example:
DF1<-data.frame("DATE"=c(as.Date("... |
H: How to make a decision tree with both continuous and categorical variables in the dataset?
Let's say I have 3 categorical and 2 continuous attributes in a dataset. How do I build a decision tree using these 5 variables?
Edit:
For categorical variables, it is easy to say that we will split them just by {yes/no} and ... |
H: Keep track of trainings, datasets eetc
After searching quite some time for it on Google I could not find a sufficient software/toolbox that can manage trainings of neural networks. I thought of a program that combines visualization techniques without the need to write code as well as having the possibility to compa... |
H: Python: Detect if data of a time series stays constant, increases or decreases
i need to analyse and later try to improve (integrate a filter) for measurement data that i compare to accurate reference data with python.
First i want to calculate the mean offset and the standard deviation of the measurement data over... |
H: Stata-style replace in Python
In Stata, I can perform a conditional replace using the following code:
replace target_var = new_value if condition_var1 == x & condition_var2 == y
What's the most pythonic way to reproduce the above on a pandas dataframe? Bonus points if I can throw the new values, and conditions int... |
H: What is the use of torch.no_grad in pytorch?
I am new to pytorch and started with this github code. I do not understand the comment in line 60-61 in the code "because weights have requires_grad=True, but we don't need to track this in autograd". I understood that we mention requires_grad=True to the variables which... |
H: GAN vs DCGAN difference
I am trying to understand the key difference between GAN and DCGAN.
I know that DCGAN uses a convolutional network. But:
What data is better to push into GAN and what data fits better to DCGAN?
Does DCGAN work better with small data dimensions?
AI: A Generative Adversarial Network (GAN) ta... |
H: RandomForest - Reasons for memory usage / consumption?
Which factors influence the memory consumption?
Is it the number of trees (n_estimators) or rather the number of data records of the training data or something other?
AI: Both the amount of data and the number of trees in your forest will take up memory storag... |
H: Does hierarchical agglomerative clustering with centroid-linkage suffer from chain-effect?
It is known that the results of hierarchical agglomerative clustering using single-link method in order to determine the inter-cluster distance suffer form the chain-effect (natural clusters tend to extend trough a line of fe... |
H: Automated Function (python)
I am trying to create a function that automates the process of taking a CSV file, splits in the data in features and responses, apply different models (regression) to the data and score them according to some metric such as MAE, RSME, etc. Model parameter should be easily interchangeable... |
H: Interactive dashboard for time series data
I'm searching for some tools that allow me to build a dashboard in order to visualize information about time series. This dashboard needs to be interactive and allows to be integrated into a web site (like a web application).
I made some projects with D3.js, but for this o... |
H: How google get the 'use over time for' data from the before internet years?
Recently I am reading a book and I found there are lots of words I rarely saw. While I was searching their meaning, I found that for a single vocabulary google has a use over time for: statistic -- from 1800 to 2010.
I may imagine how goog... |
H: How can I apply PCA to KNN?
I want to know the do not want to how to use library
I will denote a $n\times p$ data matrix by $X$, where $n<p$. That is, each row of $X$ is one sample data with $p$ feature variables.
By using singular vector decomposition method, I can decompose $X$ into $A$, $B$, and $C$ such that $... |
H: removing special character from CSV file
I read my csv file as pandas dataframe. Originally it's a dict with multiple entries per keys. Its looks like this after reading as pandas dataframe:
aad,"[1,4,77,4,0,0,0,0,3]"
bchfg,"[4,1,7,8,0,0,0,1,0]"
cad,"[1,2,7,6,0,0,0,0,3,]"
mcfg,"[0,1,0,0,0,5,0,1,1]"
so I want to fi... |
H: Using Policy Iteration on an automaton
I've read many explanation on how do to policy iteration, but I can't find an example, so I'm stuck right now trying to figure out to Policy Iteration.
The numbers next to each state show the reward received for arriving in that state. For example, if the agent started in $S_... |
H: How to make sense of confusion matrix
Consider a binary classification problem with 0 labels denoting normal and 1 abnormal or rare. The number of instances with 0 classes are more in comparison to 1. In general,
1) Does 0 always refer to positive or a negative depending on what we define as a positive and negativ... |
H: Algorithm for multiple input single output ML
As an ML newbie, I have a question. I have a set of data with 2 inputs and 1 output. I'm trying to predict the output.
input1 is an integer number, input2 is like a category between 1-5. Output is also a number.
input1=25 input2=2 output=25
input1=34 input2=2 output=35
... |
H: Train, test split of unbalanced dataset classification
I have a model that does binary classification.
My dataset is highly unbalanced, so I thought that I should balance it by undersampling before I train the model. So balance the dataset and then split it randomly. Is this the right way ? or should I balance al... |
H: Training a regression algorithm with a variable number of features
I need to train a regression algorithm with multiple features and a single label (predicted value). The problem is that this algorithm has to be able to do on-line learning and the number of features it will receive will vary. Let me give a clear ex... |
H: Error while using flow_from_generator
Getting this error while using flow_from_generator in keras
63/3851 [..............................] - ETA: 6:41:59 - loss: 12.8586 - acc: 0.1930
64/3851 [..............................] - ETA: 6:41:40 - loss: 12.8544 - acc: 0.1934Traceback (most recent call last):
File "... |
H: Why do we need the sigmoid function in logistic regression?
What is the purpose of the logistic sigmoid function as it is used in logistic regression? Why does it need to be part of the hypothesis function h(x) ?
As I understand it, the logistic sigmoid function gives the probability that a certain input vector x i... |
H: can't get variables from TF collection
Aurelion Geron's example shows how to stored selected operations in a collection, so they can then be easily accessed later:
Adding:
for op in (X, y, accuracy, training_op):
tf.add_to_collection("my_important_ops", op)
Then retrieving:
X, y, accuracy, training_op = tf.get... |
H: How to set input for proper fit with lstm?
My input training and test dataset is the following size:
print(trainX.shape):(53394, 3)
print(testX.shape):(17799, 3)
print(trainY.shape):(53394,)
print(testY.shape):(17799,)
I reshaped it as follows:
trainX.shape:(1, 53394, 3)
testX.shape: (1, 17799, 3)
trainY.shape: (1... |
H: convert list of tuple of tuple to list of tuple in pySpark
Code:
def find_collinear(rdd):
op = rdd.map( lambda x: (find_slope(x)[0][1],x) )
op = op.groupByKey().mapValues(lambda x:[a for a in x])
op = op.map(lambda x:x[1])
return op
def find_slope(x):
p1 = x[0]
p2 = x[1]
if p1[0] == p2[... |
H: Preprocessing and dropout in Autoencoders?
I am working with autoencoders and have few confusions, I am trying different autoencoders like :
fully_connected autoencoder
convolutional autoencoder
denoising autoencoder
I have two dataset , One is numerical dataset which have float and int values , Second is text da... |
H: Is it valid to include your validation data in your vocabulary for NLP?
At the moment, I am following best practices and creating a "bag of words" vector with a vocabulary from the training data. My cross validation (and test) datasets are transformed using this model, using the same vocabulary created by the train... |
H: Using Machine Learning to Predict Temperature
I am a beginner in ML and I want to create a smart thermostat, that after collecting enough data from the interaction with the user, it will start to set the home temperature by itself.
What I got so far is the hardware prototype that lets the user set the temperature, ... |
H: Visualize the predicted and actual class after training and testing
The data set X has 10 features with 50 instances labelled as 0 and 1. Considering only 6 instances as an example here, let YPred labels are [1,0,1,0,1,1] and the actual ground truth labels are YTest = [0,0,1,1,1,0]. I cannot draw a decision boundar... |
H: Making predictions from keras with SciKit
Ive been thinking about combining some processes between keras and Sci-kit Learn and am looking to the this group to either validate my process or tell Im crazy. Im creating a simple Regression problem using 17 inputs like this:
Creating test/train here:
X_train, X_test, y_... |
H: LOF gives same number of outliers irrespective of parameters
I am running lof algorithm for around 100k 2d points. Each time, I run the lof algorithm with different n_neighbours parameter, I get the same number of points as outliers. It's always 10% of the points as outliers. Is this how this algorithm is supposed ... |
H: Transfer learning by concatenating the last classification layer
Before going into an obvious XY problem, I will explain you what I'm trying to do.
I'm training a simple MobileNet pre-trained with Imagenet for multiclass classification. What I do is freeze all the convolutional part, and then create a new Predictio... |
H: Backpropagation - softmax derivative
I have a question on the backpropagation in a simple neural network (I am trying to derive the derivative for the backpropagation).
Suppose that the network is simple like so (forward pass):
$$\begin{aligned}z_1 &= xW_1 + b_1 & (1) \\
a_1 &= \tanh{(z_1)} & (2) \\
z_2 & = a_1W... |
H: Is it better to optimize hyperparameters or run multiple epochs?
Whenever I train a neural network I only have it go through a few epochs ( 1 to 3). This is because I am training them on a bad CPU and it would take some time to have the neural network go though many epochs.
However, whenever my neural network perf... |
H: Transforming words in sentences into vector form to prepare a model
I want to build a simple classifier that classifies if the text is a question or just a simple message. I understand logistic regression and can work to create a simple neural network.
I have the labeled input data in English, Japanese, Korean, Th... |
H: Making sense of how R works internally
As what type of "thing" are various objects and functions one deals frequently with in R stored internally?
To clarify: For languages like Python it is very easy to understand conceptually how your data is stored internally: Everything is stored as an object and this uniform ... |
H: Classification/Prediction based on Multivariate Time Series
So, I have a time series with many independent variables (X's) and an outcome variable Y (that I want to predict, think a 2 class logistic regression where output would either be 1 or a 0). Kindly see a sample below:
Timestamp X1 X2 X3 ... |
H: Reshaping big dataset with MinMaxScaler giving error
My data set is of shape (1249, 228). Most of the entries are zero and other are integers like 1,2,5,10,20 etc. I want to transform this set for the input into LSTM. But when I am applying MinMaxScaler. It is giving the following error:
load the dataset:
dataset1 ... |
H: Error while using the pandas_datareader package
I am trying to do a basic project where I grab some data from Morningstar or Google Finance, but when I import the package according to the usage instructions on GitHub and run Python in Pycharm, it returns the error:
ImportError: cannot import name 'is_list_like'
Wh... |
H: how can autoencoder reduce dimensionality?
I can't understand how is dimensionality reduction achieved in autoencoder since it learns to compress data from the input layer into a short code, and then uncompress that code into the original data I can' t see where is the reduction: the imput and the putput data have... |
H: Similarity between two scatter plots
I would like to know if there is a metric used to compute the similarity between two scatter plots?
AI: The simplest method is to calculate the euclidean distance between the baricenters of the two distributions; This do not take in account of the variance between the distributi... |
H: How is the property in eq 15 obtained for Xavier initialization
I am new in this field so please be gentle with terminology.
In the original paper; "Understanding the difficulty of training deep feedforward neural networks", I dont understand how equation 15 is obtained, it states that giving eq 1 :
$$
W_{ij} \sim ... |
H: Why do we double the number in a quadratic cost function or MSE?
$$ C(w,b) = \frac{1}{2n}\sum_{x}||y(x)-a||^2 $$
Where y is a 10-dimensional vector, a is the output, w is the weight and b is the bias and n is the number of inputs. If this is the MSE, shouldn't it be $\frac{1}{n}$ instead?
Link
AI: This is really ju... |
H: Why TF-IDF is working with Sentiment Analysis?
Word2vec looks excellent to me as representation of corpus for sentiment analysis. It has relations between words etc. TF-IDF has only weight of the word how important it is. Results with sentiment analysis using both of these representation are quite similar ~90%
Why ... |
H: Is this a good practice of feature engineering?
I have a practical question about feature engineering... say I want to predict house prices by using logistic regression and used a bunch of features including zip code. Then by checking the feature importance, I realize zip is a pretty good feature, so I decided to a... |
H: What does depth mean in the SqueezeNet architectural dimensions table?
First time reading the SqueezeNet paper. Based on my understanding, a fire module contains a squeeze layer of 1x1 filters and a expand layer of 1x1 and 3x3 filters. If we take fire2 for instance, the input dimension is 55x55x96 and we take 16 1x... |
H: Keras exception: ValueError: Error when checking input: expected conv2d_1_input to have shape (150, 150, 3) but got array with shape (256, 256, 3)
I am working on multiclass classification of images. For this I created a CNN model in keras. I already pre-processed all images to size (150,150,3). Here is model summa... |
H: Stratify on regression
I have worked in classification problems, and stratified cross-validation is one of the most useful and simple techniques I've found. In that case, what it means is to build a training and validation set that have the same prorportions of classes of the target variable.
I am wondering if such... |
H: Estimate battery voltage based on scheduled events and previous behaviour
My goal is to estimate if a battery will have enough charge for certain other systems to be powered. The power state of the other systems is recorded (i.e. if they are turned on or not), as well as the times when the battery is being charged ... |
H: How to customize word division in CountVectorizer?
>>> from sklearn.feature_extraction.text import CountVectorizer
>>> import numpy
>>> import pandas
>>> vectorizer = CountVectorizer()
>>> corpus1 = ['abc-@@-123','cde-@@-true','jhg-@@-hud']
>>> xtrain = vectorizer.fit_transform(corpus1)
>>> xtrain
<3x6 sparse matr... |
H: Correlate an array of categorical features to binary outcome
I have a data set that looks like this:
target,items
1,[i1,i3]
1,[i4,i5,i9]
0,[i1]
...
The variable target is 0-1 outcome. The feature "items" is a set of items (variable length). Each item is a categorical variable (one of: i1, i2, .., i_N). There's no ... |
H: XGboost - Choice made by model
i am using XGboost to predict a 2 classes target variable on insurance claims. I have a model ( training with cross validation, hyper parameters tuning etc...) i run on another dataset.
My question is :
is there a way to know why a given claim has been affected to one class i.e. the ... |
H: Correcting ALL CAPS for human and algorithmic consumption
United States federal tax returns tend to be written in ALL CAPS to facilitate OCR. This practice has persisted even when returns are filed electronically. Thus, much of the text in the IRS 990 dataset is in all caps. This makes it hard to read, and limits t... |
H: Using Mean Squared Error in Gradient Descent
I've recently been writing linear regression algorithms from scratch to gain an understanding of how the maths behind it works (something that was a bit of a black box beforehand), and so I got around to differentiating the cost function. Without realising it I used the ... |
H: How is the equation for the relation between prediction error, bias, and variance defined?
I'm reading this article Understanding the BiasVariance Tradeoff. It mentioned:
If we denote the variable we are trying to predict as $Y$ and our
covariates as $X$, we may assume that there is a relationship relating
one... |
H: Subtracting grand mean from train and test images
I am building an image classifier based off the VGG_face keras implementation. It is easiest for me to extract a csv file full of the representations and then try classifiers on those representations. When I got the representations, I first subtracted the mean of th... |
H: What approach other than Tf-Idf could I use for text-clustering using K-Means?
I am working on a text-clustering problem. My goal is to create clusters with similar context, similar talk. I have around 40 million posts from social media. To start with I have written clustering using K-Means and Tf-Idf. The followin... |
H: Toolbox for handling NaNs in Python 2.7
Is there a good toolbox for handling and analyzing missing values in Python 2.7?
There is a good toolbox for doing this in Python 3.6 here (missingno): https://github.com/ResidentMario/missingno
I need to work in Python 2.7. so, this is why I ask.
AI: First of all, visualize ... |
H: How much neural network theory required to design one?
So I have looked at some of the literature on neural networks and read some chapters, but the learning curve is so steep that I have had trouble even getting started on designing the neural network to solve my problem.
From what I understand, the architecture (... |
H: Does central limit theorem work well for Pareto distribution?
I am new to Data Science. Recently I was studying a course about statistics. One of the tasks there was to check the central limit theorem in practice.
The idea was quite simple: take a continuous random variable; generate, say, 1000 samples from it, eac... |
H: Should I eliminate all ID columns and similar columns from training data?
This is a basic question so bear my ignorance. I feel like they contribute collectively in no way to the target. This is for performance and accuracy.
The target is polar (0,1).
AI: It depends.
If your data samples are IID (independent and id... |
H: How to print a Confusion matrix from Random Forests in Python
I applied this random forest algorithm to predict a specific crime type. The example I took from this article here.
import pandas as pd
import numpy as np
from sklearn.preprocessing import LabelEncoder
import random
from sklearn.ensemble import RandomF... |
H: Can pinball loss be used to construct a prediction interval?
I'm modeling some time series data ($\{y_t\}_t$) and would like to construct a model that is able to return not just a single-value prediction $\hat{y_t}$, but an interval $C_t=(\hat{y}_{t, lower}, \hat{y}_{t, upper})$ such that $y_t \in C_t$ with some pr... |
H: How do i convert a Named num [1:4] to a data frame in R?
newbie to r, taking The R Programming Environment from coursera. one of the assignments is to select some columns from a data frame and find the means.
the code below seems to get the correct answer, but the answer should be a data frame.
wc_2 <- worldcup %>%... |
H: Generating ordinal data
I would like to generate synthetic data which are ordinal, i.e. ordered, in Python. But how would I do this? What are the differences in generating ordinal data vs categorical data?
I'm reading the paper "Automatic Discovery of the Statistical Types of Variables in a Dataset," by Valera an... |
H: On minimizing matrix norm (AB-C)
Given A, B and C are matrices with dim(A) = m x n, dim(B) = n x p and dim (C) = m x p, the problem asks to evaluate
I need to learn $$\tilde{A}$$ such that $$\min_{\tilde{A}}||\tilde{A}^TB-C||$$
and $$\min_{\tilde{A}}||\tilde{A}-A||$$
AI: In general, you can't. You can find a matrix... |
H: When is feature transformation required?
I was fitting machine learning models to clean data(Imputed missing values, removed unnecessary features etc). I didn't transform the features that are skewed. Before moving forward, I want to understand how important feature transformation is to fit data into a model. Any o... |
H: Customer-Product Analytics
I am new to Data Science and I want to make Customer Product Analytics for my company(bank). I can have a data of customers, their income, daily transactions, average balance etc and what product(saving certificates etc) they have taken according to their account balance. Can i have a pre... |
H: ValueError: not enough values to unpack (expected 4, got 2)
I have written this code
fig, (axis1, axis2,axis3, axis4)=plt.subplots(2,2,figsize=(10,4))
and I am getting this error
ValueError: not enough values to unpack (expected 4, got 2)
I tried many ways to remove this error but all was in vain.
Can you expla... |
H: Predict ratings for Item Based Collaborative Filtering
Given the (cosine) similarity score of top 100 neighbors of every item, how do I predict ratings for unrated items? Please explain in simple terms.
Item
1 260 0.577305 780 0.5655413 1210 0.5529503 3114 0.5425038 1270 .....
2 367 0.5202925 364 0.5093... |
H: Shallow Neural Net for predicting numbers other then 1 or 0?
I'm not gonna lie, I'm very new to neural networks but am also so interested in them and learning the way they work and what can be made from them. So in my endeavors for learning, I stumbled upon Siraj Ravel's youtube channel and furthermore, his Github ... |
H: Pandas index error
I am trying to use train_test_split to split my data. However, I am getting an index error. I pasted part of the error message below. I am using Python 3.5 version and sklearn 0.18.1. The code worked with my previous dataset that was different. Features here are in Pandas DataFrame and labels are... |
H: Can the learning rate be considered both a parameter AND a hyper-parameter?
Here is my understanding of those 2 terms:
Hyper-parameter: A variable that is set by a human before the training process starts. Examples are the number of hidden-layers in a Neural Network, the number of neurons in each layer, etc. Some m... |
H: What can be done to increase the accuracy of a biological dataset?
I have a biological unbalanced dataset on which I have applied deep learning, Support Vector Machine (all the kernel functions) and Artificial Neural network for multiclass classification (size: 139 samples , 5 attributes) in python. Unfortunately t... |
H: what does eta constant mean in numpy
I am using numpy to implement some neural network tutorials. There is a constant("eta") used in codes. What does it means and what it stands for?
AI: Usually "eta" means learning rate, but it would be better if you could show an example. |
H: How to use the output of GridSearch?
I'm currently working with Python and Scikit learn for classification purposes, and doing some reading around GridSearch I thought this was a great way for optimising my estimator parameters to get the best results.
My methodology is this:
Split my data into training/test.
Use ... |
H: Keras input dimension bug?
Keras has a problem with the input dimension. My first layer looks like this:
model.add(Dense(128, batch_size=1, input_shape=(150,), kernel_initializer="he_uniform", kernel_regularizer=regularizers.l2(0.01), activation="elu"))
As you can see the input dimension should be (150,) and with ... |
H: How much data warrants building a pipeline?
If I'm doing simple aggregation dashboards, what's the minimum amount of data which justifies building a full blown data processing pipeline? Is it reasonable to build a complicated pipeline with Mysql -> Hadoop -> Redshift and then analytics and visualizations on top of ... |
H: What's a good Python HMM library?
I've looked at hmmlearn but I'm not sure if it's the best one.
AI: SKLearn has an amazing array of HMM implementations, and because the library is very heavily used, odds are you can find tutorials and other StackOverflow comments about it, so definitely a good start.
http://scikit... |
H: Perceptron weight vector update
I read about the Rosenblatt Perceptron Learning Algorithm. Often there is an explicit note:
It is important to note that all weights in the weight vector are being updated simultaneously
But why are all weights updated simultaneously? I tried another approach where I iterated over ... |
H: Linear Discriminant Analysis, which parameters can be tunned in cross validation set up?
I am implementing Linear Discriminant Analysis in R, which parameters can be tunned in cross validation set up? In regularized mode called penalizedLDA there are parameters which are optimised but I want to know which parameter... |
H: Tensorflow regression model giving same prediction every time
import tensorflow as tf
x = tf.placeholder(tf.float32, [None,4]) # input vector
w1 = tf.Variable(tf.random_normal([4,2])) # weights between first and second layers
b1 = tf.Variable(tf.zeros([2])) # biases added to hidden layer
w2 = ... |
H: Which is better: Out of Bag (OOB) or Cross-Validation (CV) error estimates?
I have seen other posts in this forum but didn't find any convincing answer.
Random Forest has an another way of tuning hyperparameter via OOB by design. OOB and CV are not the same as OOB error is calculated based on a portion of trees in ... |
H: Evaluating loss for non classifying convolutional neural network
Sorry if my question is kind of dumb, I am very new to this field.
I am trying to create a CNN that plays a variant of chess (for the examples, we'll use chess as it is close enough).
My network , which is a policy network, outputs a vector of planes ... |
H: Breaking down a column in Pandas into a separate CSV for display in Tableau
My data is coming from a CSV, which should be visualized in Tableau.
However, the data contains the column category_list, which consists of values separated by a vertical bar (|).
Since Tableau can't handle arrays inside of attributes, I us... |
H: COUNT on External Table in HIVE
I have been trying around the EXTERNAL table concepts in HIVE
CREATE EXTERNAL TABLE IF NOT EXISTS MovieData
(id INT, title STRING,releasedate date, videodate date,
URL STRING,unknown TINYINT, Action TINYINT, Adventure TINYINT,
Animation TINYINT,Children TINYINT, Comedy TINYINT, Crim... |
H: Name of this algorithm for supervised cluster assignment
Is there the name for an algorithm of cluster assignment that is based uniquely on the distance between the data point to classify and the center of the cluster?
Let me be more clear:
Let's say that I have two clusters $A,B$ made by $N$ points $x(i)_A$ and $x... |
H: Binary predication from binary variables
Logistic Regression generates a binary outcome for a non-binary variable. I need a binary outcome from a binary variable. This is the requirement.
How to predict binary A using previous values of A?
or
How to predict binary A,B,C,D values from previous A,B,C,D values?
I ... |
H: What is the meaning of spherical dataset?
In the following article, one of the statement is as follows:
The K-means algorithm is effective only for spherical datasets
What does spherical dataset mean?
AI: In this case, a picture is a worth a thousand words. They literally mean data whose distribution on X,Y is ro... |
H: How does LightGBM deal with value scale?
I understand that the loss metric can be used as linear, or log, or other things. This is documented at http://lightgbm.readthedocs.io/en/latest/Parameters.html?highlight=logloss#metric-parameters
I would like to understand how LightGBM works on variables with different scal... |
H: What does a predicted probability really mean, without considering the accuracy of the underlying model?
Say I've built a (completely unrealistic) classification model in Keras that gives me 1.00 accuracy.
And next, I would like to use my model on some new, unseen data, and use model.predict_proba to get a probab... |
H: Training the Discriminative Model in Generative Adversarial Neural Network
What I know so far in DCGAN is that a discriminator is trained using the labeled data (so maybe that occurs before training the generative model). Also, I know that there is race between the generator and the discriminator, so maybe training... |
H: What feature engineering is necessary with tree based algorithms?
I understand data hygiene, which is probably the most basic feature engineering. That is making sure all your data is properly loaded, making sure N/As are treated as a special value rather than a number between -1 and 1, and tagging your categorical... |
H: Grid Search and High Variance
I am currently trying to optimise some parameters on my model (15000 samples). What I am finding is a relatively large variance in the loss function 2%-10% which makes it hard to identify which parameter is the best. This appears to happen based on how the random number generator split... |
H: Loss function in GAN
Since the aim of a Discriminator is to output 1 for real data and 0 for fake data, hence, the aim is to increase the likelihood of true data vs. fake one. In addition, since maximizing the likelihood is equivalent to minimizing the log-likelihood, why are we updating the discriminator by ascend... |
H: Why should the initialization of weights and bias be chosen around 0?
I read this:
To train our neural network, we will initialize each parameter W(l)ijWij(l) and each b(l)ibi(l) to a small random value near zero (say according to a Normal(0,ϵ2)Normal(0,ϵ2) distribution for some small ϵϵ, say 0.01)
from Stanford ... |
H: How should values that "don't exist" sometimes be handled as input data?
I'm currently training an agent to learn how to fight in a shooting game.
I'm using the bullet positions of the agent's opponent as one of the features. The features "don't exist" when the opponent isn't firing a bullet.
What should I substitu... |
H: How to use isolation forest from sklearn to return the positions of anomalies?
Assuming there is a $n$ x $m$ matrix with $n$ features and $m$ samples (each row is a feature and each column is a sample). I would like to use isolation forest in sklearn to return the positions of anomaly samples, for example, it retur... |
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